Abstract: Intrusion detection and identification of security threats are critical issues for Cyber defense. Many intrusion detection methods have been proposed. However, several important problems still remain to be explored, including how to select effective information sources for detection and how to avoid security vulnerabilities of intrusion detection systems (IDSs). In this talk, I will present an intrusion detection method using attack context information. I will also present several case studies using attack context information. Our experimental studies show that the accuracy of intrusion detection can be improved if such attack context information is used. Moreover, I will present a method for the self-protection of IDSs.

Short Bio: Dr. Jianchun Jiang is a researcher at Institute of Software in Chinese Academy of Sciences, Beijing, China. He received a Ph.D. degree in Computer Science from Institute of Software in 2001, and a B.S. and an M.S. degree in mathematics and computer science from Guangxi Normal University in 1994 and 1997, respectively. His current research areas include intrusion detection, vulnerability analysis, network worm defense, security measurement and risk analysis. He has published more than thirty papers and six books on information security. Some of his books are used as textbooks for Chinese national IT ability examination. Dr. Jiang is currently visiting NC State University.